The importance of Augmented Reality (AR) based enriching techniques is on the rise. AR-based techniques have emerged as a new channel to attract, engage, and retain customers who prefer to augment reality during their shopping experience. In the retain world, historically, individual stores may create their own AR application to promote single store products and catalogs. Such applications may be used to augment any of the products available in those individual stores over an AR compatible device for facilitating a customer's decision-making process. However, such applications only consider items that may be available at a selected store. Such applications often do not consider items that may be available at a different store.
Currently, there is no system available to a user when the user wants to augment items from more than one store and ascertain the compatibility of those items. Also, there is no system that allows stores to create promotional activities in collaboration with different stores and apply various user filters to products such as price, color, brand and the like.
Applications that may augment items onto an AR compatible medium may provide an enhanced platform for facilitating sales for any e-commerce platform however ignoring products from other e-commerce platforms may constrain the efficiency of the augmentation process. Furthermore, single source item augmentation may be not be optimized in the world of “always on” where the market landscape, technology disruption, and demand situation constantly evolve.
There is therefore a need for a system that may augment products from various stores and may perform a compatibility analysis for items augmented from various platforms. There is also a requirement for a system which helps customer and e-commerce stores to collaborate and create an end to end augmented user journeys using multiple store catalogs, multiple stores and recommend the items, promotions and the like based on the augmented data insights along with customers' previous store data insights.
Accordingly, a technical problem with the currently available procurement processes is that they may be inefficient, inaccurate, and/or not scalable. There is a need for a real time intelligence augmentation model which will consider the right set of criteria, and perform a compatibility analysis amongst various items across multiple e-commerce stores. Additionally, there is a need for a system that may facilitate multiple store collaborations, sales package generation, and the like based on the continuous sensing of emerging risks and opportunities, the evaluation of recommendations, and the rapid action/engagement opportunities of completing a sales process.